Graph Neural Networks! by @s_scardapane
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etworks
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RESEARCH
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Graph Neural Networks: Advanced Machine Learning Techniques
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OpenAI Employee Claims Company Has Already Achieved AGI
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OpenAI Employee Says They’ve "Already Achieved AGI" https://
futurism.com/openai-employe
e-claims-agi?utm_source=dlvr.it&utm_medium=bluesky
… #OpenAI #LLMs #LLM #GenerativeAI #GenAI #ChatGPT #chatgpt4 #ChatGPTTips #technology #TechRevolution #tech #Engineering @AlbertoEMachado @LavaletteAstrid @Eli_Krumova @Khulood_Almani @anand_narang -
Procedural Knowledge in Pretraining Drives LLM Reasoning
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10). Procedural Knowledge in Pretraining Drives Reasoning in LLMs – studies what documents in the pertaining influence model outputs; by looking at the pertaining data, it tries to understand better what kind of generalization strategies LLMs use to perform reasoning tasks.
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GenCast ML Weather Model Outperforms Leading Forecasting Systems
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6). GenCast – an ML weather prediction model that outperforms the world's leading operational weather forecasting system (ECMWF's ENS) in both accuracy and speed.
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Challenges in Human-Agent Communication: Establishing Common Ground
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7). Challenges in Human-Agent Communication – present a comprehensive analysis of key challenges in human-agent communication, focusing on how humans and AI agents can effectively establish common ground and mutual understanding. https://
microsoft.com/en-us/research
/uploads/prod/2024/12/HCAI_Agents.pdf
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Retrieval-Augmented Reasoning Enhances LLM Accuracy
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8). Retrieval-Augmented Reasoning for LLMs – extends the rStar reasoning framework to enhance reasoning accuracy and factual reliability of LLMs; it leverages a Monte Carlos Tree Search (MCTS) framework with explicit retrieval-augmented reasoning to produce multiple candidate
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ALAMA: Framework for Language Agents Learning Mechanisms
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4). ALAMA – a new framework that helps language agents automatically learn when to use different mechanisms (ReAct, CoT, Reflection, etc.) for automatically completing tasks, improving on current approaches that use fixed or predefined mechanisms.
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Auto-RAG: Autonomous Iterative Retrieval Model with Superior Performance
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5). Auto-RAG – an autonomous iterative retrieval model with superior performance across many datasets; Auto-RAG is a fine-tuned LLM that leverages the decision-making capabilities of an LLM.
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Reverse Thinking Improves LLM Reasoning Performance Efficiency
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3). Reverse Thinking – shows that training LLMs to learn "reverse thinking" helps to improve performance in commonsense, math, and logical reasoning tasks. It claims to outperform a standard fine-tuning method trained on 10x more forward reasoning.
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Top ML Papers Week: Genie 2, GenCast, OpenAI o1
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It was a huge week of AI and LLM papers. Here are the top ML Papers of the Week (Dec 2-8): – Genie 2
– GenCast
– OpenAI o1
– Auto-RAG
– Reverse Thinking
– Retrieval-Augmented Reasoning for LLMs Read on for more: